Exploiting global impact ordering for higher throughput in selective search

Michał Siedlaczek, Juan Rodriguez, Torsten Suel

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    We investigate potential benefits of exploiting a global impact ordering in a selective search architecture. We propose a generalized, ordering-aware version of the learning-to-rank-resources framework [9] along with a modified selection strategy. By allowing partial shard processing we are able to achieve a better initial trade-off between query cost and precision than the current state of the art. Thus, our solution is suitable for increasing query throughput during periods of peak load or in low-resource systems.

    Original languageEnglish (US)
    Title of host publicationAdvances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings
    EditorsClaudia Hauff, Norbert Fuhr, Leif Azzopardi, Djoerd Hiemstra, Benno Stein, Philipp Mayr
    PublisherSpringer Verlag
    Pages12-19
    Number of pages8
    ISBN (Print)9783030157180
    DOIs
    StatePublished - 2019
    Event41st European Conference on Information Retrieval, ECIR 2019 - Cologne, Germany
    Duration: Apr 14 2019Apr 18 2019

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume11438 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference41st European Conference on Information Retrieval, ECIR 2019
    CountryGermany
    CityCologne
    Period4/14/194/18/19

    Keywords

    • Global ordering
    • Selective search
    • Shard selection

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Computer Science(all)

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